Fatigue and non-fatigue mathematical muscle models during functional electrical stimulation of paralyzed muscle

Zhijun Cai; Er-wei Bai; Richard K Shields

doi:10.1016/j.bspc.2009.12.001

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Fatigue and non-fatigue mathematical muscle models during functional electrical stimulation of paralyzed muscle

Journal article

Peer reviewed

Fatigue and non-fatigue mathematical muscle models during functional electrical stimulation of paralyzed muscle

Zhijun Cai, Er-wei Bai and Richard K Shields

Biomedical signal processing and control, Vol.5(2), pp.87-93

2010

DOI: 10.1016/j.bspc.2009.12.001

PMCID: PMC3647619

PMID: 23667385

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Abstract

Electrical muscle stimulation demonstrates potential for preventing muscle atrophy and restoring functional movement after spinal cord injury (SCI). Control systems used to optimize delivery of electrical stimulation protocols depend upon the algorithms generated using computational models of paralyzed muscle force output. The Hill–Huxley-type model, while being highly accurate, is also very complex, making it difficult for real-time implementation. In this paper, we propose a Wiener–Hammerstein system to model the paralyzed skeletal muscle under electrical stimulus conditions. The proposed model has substantial advantages in identification algorithm analysis and implementation including computational complexity and convergence, which enable it to be used in real-time model implementation. Experimental data sets from the soleus muscles of 14 subjects with SCI were collected and tested. The simulation results show that the proposed model outperforms the Hill–Huxley-type model not only in peak force prediction, but also in fitting performance for force output of each individual stimulation train.

Electrical stimulation

Wiener–Hammerstein system

System identification

Details

Title: Subtitle: Fatigue and non-fatigue mathematical muscle models during functional electrical stimulation of paralyzed muscle
Creators: Zhijun Cai - Dept of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, United States
Er-wei Bai - Dept of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, United States
Richard K Shields - Graduate Program in Physical Therapy and Rehabilitation Science, University of Iowa, Iowa City, IA 52242, United States
Resource Type: Journal article
Publication Details: Biomedical signal processing and control, Vol.5(2), pp.87-93
DOI: 10.1016/j.bspc.2009.12.001
PMID: 23667385
PMCID: PMC3647619
NLM abbreviation: Biomed Signal Process Control
ISSN: 1746-8094
eISSN: 1746-8108
Publisher: Elsevier Ltd
Language: English
Date published: 2010
Academic Unit: Electrical and Computer Engineering; Orthopedics and Rehabilitation; Physical Therapy and Rehabilitation Science
Record Identifier: 9984047998602771

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